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Posted to commits@systemml.apache.org by gw...@apache.org on 2017/09/08 03:19:58 UTC
systemml git commit: [SYSTEMML-1605] Refresh zeppelin samples
Repository: systemml
Updated Branches:
refs/heads/master 5a2b49f20 -> 8395ffb29
[SYSTEMML-1605] Refresh zeppelin samples
Updated dependency to use release and refreshed cells.
Project: http://git-wip-us.apache.org/repos/asf/systemml/repo
Commit: http://git-wip-us.apache.org/repos/asf/systemml/commit/8395ffb2
Tree: http://git-wip-us.apache.org/repos/asf/systemml/tree/8395ffb2
Diff: http://git-wip-us.apache.org/repos/asf/systemml/diff/8395ffb2
Branch: refs/heads/master
Commit: 8395ffb29d8b502619fa667bc873182977b418dd
Parents: 5a2b49f
Author: Glenn Weidner <gw...@us.ibm.com>
Authored: Thu Sep 7 20:16:53 2017 -0700
Committer: Glenn Weidner <gw...@us.ibm.com>
Committed: Thu Sep 7 20:16:53 2017 -0700
----------------------------------------------------------------------
samples/zeppelin-notebooks/SystemML_LinearRegCG.json | 2 +-
samples/zeppelin-notebooks/tutorial1_zeppelin.json | 2 +-
2 files changed, 2 insertions(+), 2 deletions(-)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/systemml/blob/8395ffb2/samples/zeppelin-notebooks/SystemML_LinearRegCG.json
----------------------------------------------------------------------
diff --git a/samples/zeppelin-notebooks/SystemML_LinearRegCG.json b/samples/zeppelin-notebooks/SystemML_LinearRegCG.json
index 1dc91cb..49976cd 100644
--- a/samples/zeppelin-notebooks/SystemML_LinearRegCG.json
+++ b/samples/zeppelin-notebooks/SystemML_LinearRegCG.json
@@ -1 +1 @@
-{"paragraphs":[{"user":"anonymous","config":{"colWidth":12,"enabled":true,"results":{},"editorSetting":{"language":"scala"},"editorMode":"ace/mode/scala"},"settings":{"params":{},"forms":{}},"apps":[],"jobName":"paragraph_1494545879068_-1034995073","id":"20170511-163759_12734001","dateCreated":"2017-05-11T16:37:59-0700","status":"FINISHED","progressUpdateIntervalMs":500,"focus":true,"$$hashKey":"object:8101","text":"%dep\r\nz.load(\"org.apache.systemml:systemml:0.14.0-incubating\")","dateUpdated":"2017-05-11T16:38:53-0700","dateFinished":"2017-05-11T16:38:54-0700","dateStarted":"2017-05-11T16:38:53-0700","results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"res1: org.apache.zeppelin.dep.Dependency = org.apache.zeppelin.dep.Dependency@7e785cff\n"}]}},{"text":"sc.version","user":"anonymous","dateUpdated":"2017-05-11T16:38:53-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"form
s":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\nres0: String = 2.1.0\n"}]},"apps":[],"jobName":"paragraph_1494543525010_-885655540","id":"20170511-144323_52625604","dateCreated":"2017-05-11T15:58:45-0700","dateStarted":"2017-05-11T16:38:54-0700","dateFinished":"2017-05-11T16:39:07-0700","status":"FINISHED","progressUpdateIntervalMs":500,"focus":true,"$$hashKey":"object:7688"},{"text":"import org.apache.sysml.api.mlcontext._","user":"anonymous","dateUpdated":"2017-05-11T16:38:53-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\nimport org.apache.sysml.api.mlcontext._\n"}]},"apps":[],"jobName":"paragraph_1494543525011_-886040289","id":"20170511-144349_335242548","dateCreated":"2017-05-11T15:58:45-0700","dateStarted":"2017-05-11T16:38:54-0700","dateFinished":"2017-05-11T16:39:08-0700","status":"FIN
ISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:7689"},{"text":"val ml = new MLContext(sc)","user":"anonymous","dateUpdated":"2017-05-11T16:38:53-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\nml: org.apache.sysml.api.mlcontext.MLContext = org.apache.sysml.api.mlcontext.MLContext@403d1309\n"}]},"apps":[],"jobName":"paragraph_1494543525011_-886040289","id":"20170511-144600_1148672764","dateCreated":"2017-05-11T15:58:45-0700","dateStarted":"2017-05-11T16:39:08-0700","dateFinished":"2017-05-11T16:39:08-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:7690"},{"text":"ml.info","user":"anonymous","dateUpdated":"2017-05-11T16:38:53-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"
forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\n\n\n\n\n\n\n\n\n\n\n\nres1: org.apache.sysml.api.mlcontext.ProjectInfo =\nArchiver-Version: Plexus Archiver\nArtifact-Id: systemml\nBuild-Jdk: 1.8.0_121\nBuild-Time: 2017-04-19 21:45:10 UTC\nBuilt-By: asurve\nCreated-By: Apache Maven 3.3.9\nGroup-Id: org.apache.systemml\nMain-Class: org.apache.sysml.api.DMLScript\nManifest-Version: 1.0\nMinimum-Recommended-Spark-Version: 2.1.0\nVersion: 0.14.0-incubating\n"}]},"apps":[],"jobName":"paragraph_1494543525012_-887964033","id":"20170511-145343_677848491","dateCreated":"2017-05-11T15:58:45-0700","dateStarted":"2017-05-11T16:39:08-0700","dateFinished":"2017-05-11T16:39:08-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:7691"},{"text":"import org.apache.spark.mllib.util.LinearDataGenerator\nimport org.apache.spark.mllib.linalg.Vector\nimport org.apache.spark.sql._\nimport org.apache.spark.sql.types.{StructType,StructField,DoubleType,StringType
,IntegerType}","user":"anonymous","dateUpdated":"2017-05-11T16:38:54-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\nimport org.apache.spark.mllib.util.LinearDataGenerator\n\nimport org.apache.spark.mllib.linalg.Vector\n\nimport org.apache.spark.sql._\n\nimport org.apache.spark.sql.types.{StructType, StructField, DoubleType, StringType, IntegerType}\n"}]},"apps":[],"jobName":"paragraph_1494543525012_-887964033","id":"20170511-145414_1435992614","dateCreated":"2017-05-11T15:58:45-0700","dateStarted":"2017-05-11T16:39:08-0700","dateFinished":"2017-05-11T16:39:09-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:7692"},{"text":"val nRows = 1000; val nCols = 20","user":"anonymous","dateUpdated":"2017-05-11T16:38:54-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"e
nabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\n\nnRows: Int = 1000\nnCols: Int = 20\n"}]},"apps":[],"jobName":"paragraph_1494543525012_-887964033","id":"20170511-145542_2060715456","dateCreated":"2017-05-11T15:58:45-0700","dateStarted":"2017-05-11T16:39:09-0700","dateFinished":"2017-05-11T16:39:10-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:7693"},{"text":"val data = LinearDataGenerator.generateLinearRDD(sc, nRows, nCols, 0.001).toDF\nval dataX = data.select(\"features\").rdd.map{ v => Row.fromSeq(v(0).asInstanceOf[Vector].toArray)}\nval schemaX = StructType((1 to nCols).map { i => StructField(\"C\" + i, DoubleType, true) } )","user":"anonymous","dateUpdated":"2017-05-11T16:38:54-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"c
ode":"SUCCESS","msg":[{"type":"TEXT","data":"\ndata: org.apache.spark.sql.DataFrame = [label: double, features: vector]\n\ndataX: org.apache.spark.rdd.RDD[org.apache.spark.sql.Row] = MapPartitionsRDD[6] at map at <console>:41\n\nschemaX: org.apache.spark.sql.types.StructType = StructType(StructField(C1,DoubleType,true), StructField(C2,DoubleType,true), StructField(C3,DoubleType,true), StructField(C4,DoubleType,true), StructField(C5,DoubleType,true), StructField(C6,DoubleType,true), StructField(C7,DoubleType,true), StructField(C8,DoubleType,true), StructField(C9,DoubleType,true), StructField(C10,DoubleType,true), StructField(C11,DoubleType,true), StructField(C12,DoubleType,true), StructField(C13,DoubleType,true), StructField(C14,DoubleType,true), StructField(C15,DoubleType,true), StructField(C16,DoubleType,true), StructField(C17,DoubleType,true), StructField(C18,DoubleType,true), StructField(C19,DoubleType,true), StructField(C20,DoubleType,true))\n"}]},"apps":[],"jobName":"paragraph_
1494543525013_-888348782","id":"20170511-145736_384788188","dateCreated":"2017-05-11T15:58:45-0700","dateStarted":"2017-05-11T16:39:10-0700","dateFinished":"2017-05-11T16:39:14-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:7694"},{"text":"val X = spark.createDataFrame(dataX,schemaX)\nval y = data.select(\"label\")","user":"anonymous","dateUpdated":"2017-05-11T16:38:54-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\nX: org.apache.spark.sql.DataFrame = [C1: double, C2: double ... 18 more fields]\n\ny: org.apache.spark.sql.DataFrame = [label: double]\n"}]},"apps":[],"jobName":"paragraph_1494543525013_-888348782","id":"20170511-150007_1200854412","dateCreated":"2017-05-11T15:58:45-0700","dateStarted":"2017-05-11T16:39:10-0700","dateFinished":"2017-05-11T16:39:15-0700","status":"FINISHE
D","progressUpdateIntervalMs":500,"$$hashKey":"object:7695"},{"text":"val LinRegCgDML = ScriptFactory.dmlFromResource(\"/scripts/algorithms/LinearRegCG.dml\")","user":"anonymous","dateUpdated":"2017-05-11T16:38:54-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\n\n\n\n\n\nLinRegCgDML: org.apache.sysml.api.mlcontext.Script =\nInputs:\nNone\n\nOutputs:\nNone\n"}]},"apps":[],"jobName":"paragraph_1494543525014_-887194535","id":"20170511-150116_450421311","dateCreated":"2017-05-11T15:58:45-0700","dateStarted":"2017-05-11T16:39:14-0700","dateFinished":"2017-05-11T16:39:15-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:7696"},{"text":"val LinRegCg = LinRegCgDML.in(\"X\", X).in(\"y\", y).out(\"beta_out\")","user":"anonymous","dateUpdated":"2017-05-11T16:38:54-0700","config":{"colWidth":12,"e
ditorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\n\n\n\n\n\n\nLinRegCg: org.apache.sysml.api.mlcontext.Script =\nInputs:\n [1] (Dataset as Matrix) X: [C1: double, C2: double ... 18 more fields]\n [2] (Dataset as Matrix) y: [label: double]\n\nOutputs:\n [1] beta_out\n"}]},"apps":[],"jobName":"paragraph_1494543525014_-887194535","id":"20170511-150143_1437310013","dateCreated":"2017-05-11T15:58:45-0700","dateStarted":"2017-05-11T16:39:15-0700","dateFinished":"2017-05-11T16:39:17-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:7697"},{"text":"val res = ml.execute(LinRegCg)","user":"anonymous","dateUpdated":"2017-05-11T16:38:54-0700","config":{"tableHide":false,"editorSetting":{"language":"scala"},"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true},"settings":{"params":{},"forms":{}},"results":{"co
de":"SUCCESS","msg":[{"type":"TEXT","data":"\n\nres: org.apache.sysml.api.mlcontext.MLResults =\n [1] (Matrix) beta_out: MatrixObject: scratch_space//_p10760_172.16.189.91//_t0/temp19_77, [20 x 1, nnz=20, blocks (1000 x 1000)], binaryblock, dirty\n"}]},"apps":[],"jobName":"paragraph_1494543525015_-887579284","id":"20170511-150218_888522247","dateCreated":"2017-05-11T15:58:45-0700","dateStarted":"2017-05-11T16:39:16-0700","dateFinished":"2017-05-11T16:39:19-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:7698"},{"text":"z.show(res.getDataFrame(\"beta_out\").sort(\"__INDEX\"))","user":"anonymous","dateUpdated":"2017-05-11T16:38:55-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TABLE","data":"__INDEX\tC1\n1.0\t0.22758923148653765\n2.0\t0.18325331678413073\n3.0\t-0.19132020477989198\n4.0\t-0.222978646
6645596\n5.0\t0.1655320728089567\n6.0\t0.4034581825273427\n7.0\t-0.13119697771587355\n8.0\t-0.22422151776382496\n9.0\t-0.03640812970196472\n10.0\t0.28305615669741196\n11.0\t0.41935757104525073\n12.0\t-0.06348947505950103\n13.0\t0.24988033284537162\n14.0\t-0.11344894712988449\n15.0\t-0.32272205772821355\n16.0\t0.09442021705906962\n17.0\t-0.29017864948719196\n18.0\t0.32589380033203724\n19.0\t-0.32768681591496096\n20.0\t0.08744302957224545\n"}]},"apps":[],"jobName":"paragraph_1494543525016_-889503029","id":"20170511-150414_1824148477","dateCreated":"2017-05-11T15:58:45-0700","dateStarted":"2017-05-11T16:39:17-0700","dateFinished":"2017-05-11T16:39:20-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:7699"},{"text":"","user":"anonymous","dateUpdated":"2017-05-11T16:18:22-0700","config":{"colWidth":12,"enabled":true,"results":{},"editorSetting":{"language":"scala"},"editorMode":"ace/mode/scala"},"settings":{"params":{},"forms":{}},"apps":[],"jobName":"paragraph
_1494543525016_-889503029","id":"20170511-154623_2118188057","dateCreated":"2017-05-11T15:58:45-0700","status":"FINISHED","errorMessage":"","progressUpdateIntervalMs":500,"$$hashKey":"object:7700"}],"name":"SystemML_LinearRegCG","id":"2CFKY21GZ","angularObjects":{"2CEM2EBHQ:shared_process":[]},"config":{"looknfeel":"default","personalizedMode":"false"},"info":{}}
\ No newline at end of file
+{"paragraphs":[{"text":"%dep\r\nz.load(\"org.apache.systemml:systemml:RELEASE\")","user":"admin","dateUpdated":"2017-09-07T18:30:43-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"res1: org.apache.zeppelin.dep.Dependency = org.apache.zeppelin.dep.Dependency@58bb9cf2\n"}]},"apps":[],"jobName":"paragraph_1504834165324_-1801375864","id":"20170511-163759_12734001","dateCreated":"2017-09-07T18:29:25-0700","dateStarted":"2017-09-07T18:30:44-0700","dateFinished":"2017-09-07T18:30:44-0700","status":"FINISHED","progressUpdateIntervalMs":500,"focus":true,"$$hashKey":"object:6022"},{"text":"sc.version","user":"admin","dateUpdated":"2017-09-07T19:39:47-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{
"code":"SUCCESS","msg":[{"type":"TEXT","data":"\nres0: String = 2.1.1.2.6.1.0-129\n"}]},"apps":[],"jobName":"paragraph_1504834165324_-1801375864","id":"20170511-144323_52625604","dateCreated":"2017-09-07T18:29:25-0700","dateStarted":"2017-09-07T19:39:47-0700","dateFinished":"2017-09-07T19:40:14-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:6023"},{"text":"import org.apache.sysml.api.mlcontext._","user":"admin","dateUpdated":"2017-09-07T19:40:20-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\nimport org.apache.sysml.api.mlcontext._\n"}]},"apps":[],"jobName":"paragraph_1504834165325_-1801760613","id":"20170511-144349_335242548","dateCreated":"2017-09-07T18:29:25-0700","dateStarted":"2017-09-07T19:40:20-0700","dateFinished":"2017-09-07T19:40:21-0700","status":"FINISHED","progressUpdat
eIntervalMs":500,"$$hashKey":"object:6024"},{"text":"val ml = new MLContext(sc)","user":"admin","dateUpdated":"2017-09-07T19:40:24-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\nml: org.apache.sysml.api.mlcontext.MLContext = org.apache.sysml.api.mlcontext.MLContext@465f5774\n"}]},"apps":[],"jobName":"paragraph_1504834165325_-1801760613","id":"20170511-144600_1148672764","dateCreated":"2017-09-07T18:29:25-0700","dateStarted":"2017-09-07T19:40:24-0700","dateFinished":"2017-09-07T19:40:24-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:6025"},{"text":"ml.info","user":"admin","dateUpdated":"2017-09-07T19:40:28-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code"
:"SUCCESS","msg":[{"type":"TEXT","data":"\n\n\n\n\n\n\n\n\n\n\n\nres1: org.apache.sysml.api.mlcontext.ProjectInfo =\nArchiver-Version: Plexus Archiver\nArtifact-Id: systemml\nBuild-Jdk: 1.8.0_121\nBuild-Time: 2017-09-05 18:30:16 UTC\nBuilt-By: asurve\nCreated-By: Apache Maven 3.3.9\nGroup-Id: org.apache.systemml\nMain-Class: org.apache.sysml.api.DMLScript\nManifest-Version: 1.0\nMinimum-Recommended-Spark-Version: 2.1.0\nVersion: 0.15.0\n"}]},"apps":[],"jobName":"paragraph_1504834165325_-1801760613","id":"20170511-145343_677848491","dateCreated":"2017-09-07T18:29:25-0700","dateStarted":"2017-09-07T19:40:28-0700","dateFinished":"2017-09-07T19:40:28-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:6026"},{"text":"import org.apache.spark.mllib.util.LinearDataGenerator\nimport org.apache.spark.mllib.linalg.Vector\nimport org.apache.spark.sql._\nimport org.apache.spark.sql.types.{StructType,StructField,DoubleType,StringType,IntegerType}","dateUpdated":"2017-09-
07T19:40:34-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\nimport org.apache.spark.mllib.util.LinearDataGenerator\n\nimport org.apache.spark.mllib.linalg.Vector\n\nimport org.apache.spark.sql._\n\nimport org.apache.spark.sql.types.{StructType, StructField, DoubleType, StringType, IntegerType}\n"}]},"apps":[],"jobName":"paragraph_1504834165326_-1800606367","id":"20170511-145414_1435992614","dateCreated":"2017-09-07T18:29:25-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:6027","user":"admin","dateFinished":"2017-09-07T19:40:35-0700","dateStarted":"2017-09-07T19:40:34-0700"},{"text":"val nRows = 1000; val nCols = 20","dateUpdated":"2017-09-07T19:40:39-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings
":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\n\nnRows: Int = 1000\nnCols: Int = 20\n"}]},"apps":[],"jobName":"paragraph_1504834165326_-1800606367","id":"20170511-145542_2060715456","dateCreated":"2017-09-07T18:29:25-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:6028","user":"admin","dateFinished":"2017-09-07T19:40:39-0700","dateStarted":"2017-09-07T19:40:39-0700"},{"text":"val data = LinearDataGenerator.generateLinearRDD(sc, nRows, nCols, 0.001).toDF\nval dataX = data.select(\"features\").rdd.map{ v => Row.fromSeq(v(0).asInstanceOf[Vector].toArray)}\nval schemaX = StructType((1 to nCols).map { i => StructField(\"C\" + i, DoubleType, true) } )","dateUpdated":"2017-09-07T19:40:43-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\ndata: org.apache
.spark.sql.DataFrame = [label: double, features: vector]\n\ndataX: org.apache.spark.rdd.RDD[org.apache.spark.sql.Row] = MapPartitionsRDD[6] at map at <console>:41\n\nschemaX: org.apache.spark.sql.types.StructType = StructType(StructField(C1,DoubleType,true), StructField(C2,DoubleType,true), StructField(C3,DoubleType,true), StructField(C4,DoubleType,true), StructField(C5,DoubleType,true), StructField(C6,DoubleType,true), StructField(C7,DoubleType,true), StructField(C8,DoubleType,true), StructField(C9,DoubleType,true), StructField(C10,DoubleType,true), StructField(C11,DoubleType,true), StructField(C12,DoubleType,true), StructField(C13,DoubleType,true), StructField(C14,DoubleType,true), StructField(C15,DoubleType,true), StructField(C16,DoubleType,true), StructField(C17,DoubleType,true), StructField(C18,DoubleType,true), StructField(C19,DoubleType,true), StructField(C20,DoubleType,true))\n"}]},"apps":[],"jobName":"paragraph_1504834165327_-1800991116","id":"20170511-145736_384788188","da
teCreated":"2017-09-07T18:29:25-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:6029","user":"admin","dateFinished":"2017-09-07T19:40:49-0700","dateStarted":"2017-09-07T19:40:43-0700"},{"text":"val X = spark.createDataFrame(dataX,schemaX)\nval y = data.select(\"label\")","dateUpdated":"2017-09-07T19:41:01-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\nX: org.apache.spark.sql.DataFrame = [C1: double, C2: double ... 18 more fields]\n\ny: org.apache.spark.sql.DataFrame = [label: double]\n"}]},"apps":[],"jobName":"paragraph_1504834165327_-1800991116","id":"20170511-150007_1200854412","dateCreated":"2017-09-07T18:29:25-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:6030","user":"admin","dateFinished":"2017-09-07T19:41:02-0700","dateStarted":"2017-09-07T19:41
:01-0700"},{"text":"val LinRegCgDML = ScriptFactory.dmlFromResource(\"/scripts/algorithms/LinearRegCG.dml\")","dateUpdated":"2017-09-07T19:41:06-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\n\n\n\n\n\nLinRegCgDML: org.apache.sysml.api.mlcontext.Script =\nInputs:\nNone\n\nOutputs:\nNone\n"}]},"apps":[],"jobName":"paragraph_1504834165327_-1800991116","id":"20170511-150116_450421311","dateCreated":"2017-09-07T18:29:25-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:6031","user":"admin","dateFinished":"2017-09-07T19:41:06-0700","dateStarted":"2017-09-07T19:41:06-0700"},{"text":"val LinRegCg = LinRegCgDML.in(\"X\", X).in(\"y\", y).out(\"beta_out\")","dateUpdated":"2017-09-07T19:41:10-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":
{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\n\n\n\n\n\n\nLinRegCg: org.apache.sysml.api.mlcontext.Script =\nInputs:\n [1] (Dataset as Matrix) X: [C1: double, C2: double ... 18 more fields]\n [2] (Dataset as Matrix) y: [label: double]\n\nOutputs:\n [1] beta_out\n"}]},"apps":[],"jobName":"paragraph_1504834165328_-1790602895","id":"20170511-150143_1437310013","dateCreated":"2017-09-07T18:29:25-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:6032","user":"admin","dateFinished":"2017-09-07T19:41:18-0700","dateStarted":"2017-09-07T19:41:10-0700"},{"text":"val res = ml.execute(LinRegCg)","dateUpdated":"2017-09-07T19:41:24-0700","config":{"tableHide":false,"editorSetting":{"language":"scala"},"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\n\nres: org.apache.sysml.api.m
lcontext.MLResults =\n [1] (Matrix) beta_out: MatrixObject: scratch_space//_p3077_172.16.203.113//_t0/temp17_75, [20 x 1, nnz=20, blocks (1000 x 1000)], binaryblock, dirty\n"}]},"apps":[],"jobName":"paragraph_1504834165328_-1790602895","id":"20170511-150218_888522247","dateCreated":"2017-09-07T18:29:25-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:6033","user":"admin","dateFinished":"2017-09-07T19:41:28-0700","dateStarted":"2017-09-07T19:41:24-0700"},{"text":"z.show(res.getDataFrame(\"beta_out\").sort(\"__INDEX\"))","dateUpdated":"2017-09-07T19:41:51-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TABLE","data":"__INDEX\tC1\n1.0\t0.22758923148653765\n2.0\t0.18325331678413073\n3.0\t-0.19132020477989198\n4.0\t-0.2229786466645596\n5.0\t0.1655320728089567\n6.0\t0.4034581825273427\n7.0\t-0.13119697771
587355\n8.0\t-0.22422151776382496\n9.0\t-0.03640812970196472\n10.0\t0.28305615669741196\n11.0\t0.41935757104525073\n12.0\t-0.06348947505950103\n13.0\t0.24988033284537162\n14.0\t-0.11344894712988449\n15.0\t-0.32272205772821355\n16.0\t0.09442021705906962\n17.0\t-0.29017864948719196\n18.0\t0.32589380033203724\n19.0\t-0.32768681591496096\n20.0\t0.08744302957224545\n"}]},"apps":[],"jobName":"paragraph_1504834165329_-1790987644","id":"20170511-150414_1824148477","dateCreated":"2017-09-07T18:29:25-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:6034","user":"admin","dateFinished":"2017-09-07T19:41:53-0700","dateStarted":"2017-09-07T19:41:51-0700"},{"text":"","dateUpdated":"2017-09-07T18:29:25-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"apps":[],"jobName":"paragraph_1504834165329_-1790987644","id":"20170511-154623_2118188057","dateCreated":"2017
-09-07T18:29:25-0700","status":"READY","errorMessage":"","progressUpdateIntervalMs":500,"$$hashKey":"object:6035"}],"name":"SystemML_LinearRegCG","id":"2CUM2XM1D","angularObjects":{"2CK6XR78M:shared_process":[],"2CHZ7WYCF:shared_process":[],"2CKFJ7WPQ:shared_process":[],"2CKFPUHJ2:shared_process":[],"2C4U48MY3_spark2:shared_process":[]},"config":{"looknfeel":"default","personalizedMode":"false"},"info":{}}
\ No newline at end of file
http://git-wip-us.apache.org/repos/asf/systemml/blob/8395ffb2/samples/zeppelin-notebooks/tutorial1_zeppelin.json
----------------------------------------------------------------------
diff --git a/samples/zeppelin-notebooks/tutorial1_zeppelin.json b/samples/zeppelin-notebooks/tutorial1_zeppelin.json
index e71b58c..840c31e 100644
--- a/samples/zeppelin-notebooks/tutorial1_zeppelin.json
+++ b/samples/zeppelin-notebooks/tutorial1_zeppelin.json
@@ -1 +1 @@
-{"paragraphs":[{"text":"%dep\r\nz.load(\"org.apache.systemml:systemml:0.14.0-incubating\")","user":"anonymous","dateUpdated":"2017-05-12T11:44:50-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":[{"graph":{"mode":"table","height":300,"optionOpen":false,"keys":[],"values":[],"groups":[],"scatter":{}}}],"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"res0: org.apache.zeppelin.dep.Dependency = org.apache.zeppelin.dep.Dependency@433ae9fc\n"}]},"apps":[],"jobName":"paragraph_1494610315765_971105361","id":"20160407-210154_742995576","dateCreated":"2017-05-12T10:31:55-0700","dateStarted":"2017-05-12T11:44:50-0700","dateFinished":"2017-05-12T11:45:00-0700","status":"FINISHED","progressUpdateIntervalMs":500,"focus":true,"$$hashKey":"object:5689"},{"text":"sc","user":"anonymous","dateUpdated":"2017-05-12T11:45:12-0700","config":{"colWidth":12,"enabled":true,"results":{},"
editorSetting":{"language":"scala"},"editorMode":"ace/mode/scala"},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\nres0: org.apache.spark.SparkContext = org.apache.spark.SparkContext@167bdf90\n"}]},"apps":[],"jobName":"paragraph_1494614606357_-213824970","id":"20170512-114326_719701142","dateCreated":"2017-05-12T11:43:26-0700","dateStarted":"2017-05-12T11:45:12-0700","dateFinished":"2017-05-12T11:45:24-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:5690"},{"text":"sc.version","user":"anonymous","dateUpdated":"2017-05-12T11:45:29-0700","config":{"colWidth":12,"enabled":true,"results":{},"editorSetting":{"language":"scala"},"editorMode":"ace/mode/scala"},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\nres1: String = 2.1.0\n"}]},"apps":[],"jobName":"paragraph_1494610556791_-90095047","id":"20170512-103556_1836482719","dateCreated":"2017-05-12T10:35:56-0700","dat
eStarted":"2017-05-12T11:45:29-0700","dateFinished":"2017-05-12T11:45:29-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:5691"},{"text":"spark","user":"anonymous","dateUpdated":"2017-05-12T11:45:32-0700","config":{"colWidth":12,"enabled":true,"results":{},"editorSetting":{"language":"scala"},"editorMode":"ace/mode/scala"},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\nres2: org.apache.spark.sql.SparkSession = org.apache.spark.sql.SparkSession@5fb3d950\n"}]},"apps":[],"jobName":"paragraph_1494612059615_-422958685","id":"20170512-110059_619823343","dateCreated":"2017-05-12T11:00:59-0700","dateStarted":"2017-05-12T11:45:32-0700","dateFinished":"2017-05-12T11:45:32-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:5692"},{"text":"import org.apache.sysml.api.mlcontext._\nimport org.apache.sysml.api.mlcontext.ScriptFactory._","user":"anonymous","dateUpdated":"2017-05-12T11:45:35-0700",
"config":{"colWidth":12,"editorMode":"ace/mode/scala","results":[{"graph":{"mode":"table","height":300,"optionOpen":false,"keys":[],"values":[],"groups":[],"scatter":{}}}],"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\nimport org.apache.sysml.api.mlcontext._\n\nimport org.apache.sysml.api.mlcontext.ScriptFactory._\n"}]},"apps":[],"jobName":"paragraph_1494610315766_972259607","id":"20160407-210407_1127760007","dateCreated":"2017-05-12T10:31:55-0700","dateStarted":"2017-05-12T11:45:35-0700","dateFinished":"2017-05-12T11:45:35-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:5693"},{"text":"val ml = new MLContext(spark)","user":"anonymous","dateUpdated":"2017-05-12T11:45:42-0700","config":{"colWidth":12,"enabled":true,"results":{},"editorSetting":{"language":"scala"},"editorMode":"ace/mode/scala"},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCES
S","msg":[{"type":"TEXT","data":"\nml: org.apache.sysml.api.mlcontext.MLContext = org.apache.sysml.api.mlcontext.MLContext@56f9544e\n"}]},"apps":[],"jobName":"paragraph_1494612075970_1862095681","id":"20170512-110115_978861967","dateCreated":"2017-05-12T11:01:15-0700","dateStarted":"2017-05-12T11:45:42-0700","dateFinished":"2017-05-12T11:45:42-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:5694"},{"text":"import org.apache.spark.sql._\nimport org.apache.spark.sql.types.{StructType,StructField,DoubleType}\nimport scala.util.Random\n\nval numRows = 1000\nval numCols = 100\nval data = sc.parallelize(0 to numRows-1).map { _ => Row.fromSeq(Seq.fill(numCols)(Random.nextDouble)) }\nval schema = StructType((0 to numCols-1).map { i => StructField(\"C\" + i, DoubleType, true) } )\nval df = sqlContext.createDataFrame(data, schema)","user":"anonymous","dateUpdated":"2017-05-12T11:45:45-0700","config":{"colWidth":12,"enabled":true,"results":{},"editorSetting":{"lang
uage":"scala"},"editorMode":"ace/mode/scala"},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\nimport org.apache.spark.sql._\n\nimport org.apache.spark.sql.types.{StructType, StructField, DoubleType}\n\nimport scala.util.Random\n\nnumRows: Int = 1000\n\nnumCols: Int = 100\n\ndata: org.apache.spark.rdd.RDD[org.apache.spark.sql.Row] = MapPartitionsRDD[1] at map at <console>:42\nschema: org.apache.spark.sql.types.StructType = StructType(StructField(C0,DoubleType,true), StructField(C1,DoubleType,true), StructField(C2,DoubleType,true), StructField(C3,DoubleType,true), StructField(C4,DoubleType,true), StructField(C5,DoubleType,true), StructField(C6,DoubleType,true), StructField(C7,DoubleType,true), StructField(C8,DoubleType,true), StructField(C9,DoubleType,true), StructField(C10,DoubleType,true), StructField(C11,DoubleType,true), StructField(C12,DoubleType,true), StructField(C13,DoubleType,true), StructField(C14,DoubleType,true), StructField(
C15,DoubleType,true), StructField(C16,DoubleType,true), StructField(C17,DoubleType,true), StructField(C18,DoubleType,true), StructField(C19,DoubleType,true), StructField(C20,DoubleType,true), StructField(C21,DoubleType,true), ...\ndf: org.apache.spark.sql.DataFrame = [C0: double, C1: double ... 98 more fields]\n"}]},"apps":[],"jobName":"paragraph_1494613302223_333591160","id":"20170512-112142_1828353367","dateCreated":"2017-05-12T11:21:42-0700","dateStarted":"2017-05-12T11:45:45-0700","dateFinished":"2017-05-12T11:45:51-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:5695"},{"text":"val minMaxMean =\n\"\"\"\nminOut = min(Xin)\nmaxOut = max(Xin)\nmeanOut = mean(Xin)\n\"\"\"","user":"anonymous","dateUpdated":"2017-05-12T11:45:55-0700","config":{"colWidth":12,"enabled":true,"results":{},"editorSetting":{"language":"scala"},"editorMode":"ace/mode/scala"},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\n\n\n\n\n\
nminMaxMean: String =\n\"\nminOut = min(Xin)\nmaxOut = max(Xin)\nmeanOut = mean(Xin)\n\"\n"}]},"apps":[],"jobName":"paragraph_1494613973746_1554581666","id":"20170512-113253_943926853","dateCreated":"2017-05-12T11:32:53-0700","dateStarted":"2017-05-12T11:45:55-0700","dateFinished":"2017-05-12T11:45:55-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:5696"},{"text":"val mm = new MatrixMetadata(numRows, numCols)\nval minMaxMeanScript = dml(minMaxMean).in(\"Xin\", df, mm).out(\"minOut\", \"maxOut\", \"meanOut\")","user":"anonymous","dateUpdated":"2017-05-12T11:46:01-0700","config":{"colWidth":12,"enabled":true,"results":{},"editorSetting":{"language":"scala"},"editorMode":"ace/mode/scala"},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\nmm: org.apache.sysml.api.mlcontext.MatrixMetadata = rows: 1000, columns: 100, non-zeros: None, rows per block: None, columns per block: None\n\n\n\n\n\n\n\n\nminMaxMeanScript: o
rg.apache.sysml.api.mlcontext.Script =\nInputs:\n [1] (Dataset as Matrix) Xin: [C0: double, C1: double ... 98 more fields]\n\nOutputs:\n [1] minOut\n [2] maxOut\n [3] meanOut\n"}]},"apps":[],"jobName":"paragraph_1494614017051_-917622","id":"20170512-113337_768342478","dateCreated":"2017-05-12T11:33:37-0700","dateStarted":"2017-05-12T11:46:01-0700","dateFinished":"2017-05-12T11:46:06-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:5697"},{"text":"val (min, max, mean) = ml.execute(minMaxMeanScript).getTuple[Double, Double, Double](\"minOut\", \"maxOut\", \"meanOut\")","user":"anonymous","dateUpdated":"2017-05-12T11:46:13-0700","config":{"colWidth":12,"enabled":true,"results":{},"editorSetting":{"language":"scala"},"editorMode":"ace/mode/scala"},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\n\n\nmin: Double = 2.2701668049962542E-5\nmax: Double = 0.9999982074959571\nmean: Double = 0.49901354112086954\n"}]}
,"apps":[],"jobName":"paragraph_1494614064744_-751901503","id":"20170512-113424_1524717418","dateCreated":"2017-05-12T11:34:24-0700","dateStarted":"2017-05-12T11:46:13-0700","dateFinished":"2017-05-12T11:46:15-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:5698"},{"user":"anonymous","dateUpdated":"2017-05-12T11:44:01-0700","config":{"colWidth":12,"graph":{"mode":"table","height":300,"optionOpen":false,"keys":[],"values":[],"groups":[],"scatter":{}},"enabled":true,"results":{},"editorSetting":{"language":"scala"},"editorMode":"ace/mode/scala"},"settings":{"params":{},"forms":{}},"apps":[],"jobName":"paragraph_1494610315774_969181616","id":"20160407-215102_2146717979","dateCreated":"2017-05-12T10:31:55-0700","status":"READY","errorMessage":"","progressUpdateIntervalMs":500,"$$hashKey":"object:5699"}],"name":"tutorial1_zeppelin","id":"2CEYWMUA2","angularObjects":{"2CEM2EBHQ:shared_process":[]},"config":{"looknfeel":"default","personalizedMode":"false"},"in
fo":{}}
\ No newline at end of file
+{"paragraphs":[{"text":"%dep\r\nz.load(\"org.apache.systemml:systemml:RELEASE\")","user":"admin","dateUpdated":"2017-09-07T18:26:48-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":[{"graph":{"mode":"table","height":300,"optionOpen":false,"keys":[],"values":[],"groups":[],"scatter":{}}}],"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"res0: org.apache.zeppelin.dep.Dependency = org.apache.zeppelin.dep.Dependency@1a0154b2\n"}]},"apps":[],"jobName":"paragraph_1504833929750_-1777827916","id":"20160407-210154_742995576","dateCreated":"2017-09-07T18:25:29-0700","dateStarted":"2017-09-07T18:26:49-0700","dateFinished":"2017-09-07T18:27:04-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:10205"},{"text":"sc","dateUpdated":"2017-09-07T20:00:06-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting
":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\nres0: org.apache.spark.SparkContext = org.apache.spark.SparkContext@3fc93211\n"}]},"apps":[],"jobName":"paragraph_1504833929752_-1780136410","id":"20170512-114326_719701142","dateCreated":"2017-09-07T18:25:29-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:10206","user":"admin","dateFinished":"2017-09-07T20:00:29-0700","dateStarted":"2017-09-07T20:00:06-0700"},{"text":"sc.version","dateUpdated":"2017-09-07T20:00:32-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\nres1: String = 2.1.1.2.6.1.0-129\n"}]},"apps":[],"jobName":"paragraph_1504833929752_-1780136410","id":"20170512-103556_1836482719","dateCreated":"2017-09-07T18:25:29-0700","status":"FINISHED","progressUpdate
IntervalMs":500,"$$hashKey":"object:10207","user":"admin","dateFinished":"2017-09-07T20:00:33-0700","dateStarted":"2017-09-07T20:00:32-0700"},{"text":"spark","dateUpdated":"2017-09-07T20:00:38-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\nres2: org.apache.spark.sql.SparkSession = org.apache.spark.sql.SparkSession@3e9bcf34\n"}]},"apps":[],"jobName":"paragraph_1504833929753_-1780521159","id":"20170512-110059_619823343","dateCreated":"2017-09-07T18:25:29-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:10208","user":"admin","dateFinished":"2017-09-07T20:00:38-0700","dateStarted":"2017-09-07T20:00:38-0700"},{"text":"import org.apache.sysml.api.mlcontext._\nimport org.apache.sysml.api.mlcontext.ScriptFactory._","dateUpdated":"2017-09-07T20:00:41-0700","config":{"colWidth":12,"editorMode"
:"ace/mode/scala","results":[{"graph":{"mode":"table","height":300,"optionOpen":false,"keys":[],"values":[],"groups":[],"scatter":{}}}],"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\nimport org.apache.sysml.api.mlcontext._\n\nimport org.apache.sysml.api.mlcontext.ScriptFactory._\n"}]},"apps":[],"jobName":"paragraph_1504833929753_-1780521159","id":"20160407-210407_1127760007","dateCreated":"2017-09-07T18:25:29-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:10209","user":"admin","dateFinished":"2017-09-07T20:00:41-0700","dateStarted":"2017-09-07T20:00:41-0700"},{"text":"val ml = new MLContext(spark)","dateUpdated":"2017-09-07T20:00:46-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\nml
: org.apache.sysml.api.mlcontext.MLContext = org.apache.sysml.api.mlcontext.MLContext@7fd9882b\n"}]},"apps":[],"jobName":"paragraph_1504833929753_-1780521159","id":"20170512-110115_978861967","dateCreated":"2017-09-07T18:25:29-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:10210","user":"admin","dateFinished":"2017-09-07T20:00:47-0700","dateStarted":"2017-09-07T20:00:46-0700"},{"user":"admin","config":{"colWidth":12,"enabled":true,"results":{},"editorSetting":{"language":"scala"},"editorMode":"ace/mode/scala"},"settings":{"params":{},"forms":{}},"apps":[],"jobName":"paragraph_1504839755386_2117456363","id":"20170907-200235_646365534","dateCreated":"2017-09-07T20:02:35-0700","status":"FINISHED","progressUpdateIntervalMs":500,"focus":true,"$$hashKey":"object:11429","text":"ml.info","dateUpdated":"2017-09-07T20:02:43-0700","dateFinished":"2017-09-07T20:02:43-0700","dateStarted":"2017-09-07T20:02:43-0700","results":{"code":"SUCCESS","msg":[{"type":"TEXT","d
ata":"\n\n\n\n\n\n\n\n\n\n\n\nres4: org.apache.sysml.api.mlcontext.ProjectInfo =\nArchiver-Version: Plexus Archiver\nArtifact-Id: systemml\nBuild-Jdk: 1.8.0_121\nBuild-Time: 2017-09-05 18:30:16 UTC\nBuilt-By: asurve\nCreated-By: Apache Maven 3.3.9\nGroup-Id: org.apache.systemml\nMain-Class: org.apache.sysml.api.DMLScript\nManifest-Version: 1.0\nMinimum-Recommended-Spark-Version: 2.1.0\nVersion: 0.15.0\n"}]}},{"text":"import org.apache.spark.sql._\nimport org.apache.spark.sql.types.{StructType,StructField,DoubleType}\nimport scala.util.Random\n\nval numRows = 1000\nval numCols = 100\nval data = sc.parallelize(0 to numRows-1).map { _ => Row.fromSeq(Seq.fill(numCols)(Random.nextDouble)) }\nval schema = StructType((0 to numCols-1).map { i => StructField(\"C\" + i, DoubleType, true) } )\nval df = sqlContext.createDataFrame(data, schema)","dateUpdated":"2017-09-07T20:00:51-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"
scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\nimport org.apache.spark.sql._\n\nimport org.apache.spark.sql.types.{StructType, StructField, DoubleType}\n\nimport scala.util.Random\n\nnumRows: Int = 1000\n\nnumCols: Int = 100\n\ndata: org.apache.spark.rdd.RDD[org.apache.spark.sql.Row] = MapPartitionsRDD[1] at map at <console>:42\nschema: org.apache.spark.sql.types.StructType = StructType(StructField(C0,DoubleType,true), StructField(C1,DoubleType,true), StructField(C2,DoubleType,true), StructField(C3,DoubleType,true), StructField(C4,DoubleType,true), StructField(C5,DoubleType,true), StructField(C6,DoubleType,true), StructField(C7,DoubleType,true), StructField(C8,DoubleType,true), StructField(C9,DoubleType,true), StructField(C10,DoubleType,true), StructField(C11,DoubleType,true), StructField(C12,DoubleType,true), StructField(C13,DoubleType,true), StructField(C14,DoubleType,true), StructField(C15,DoubleType,true), StructField(C16
,DoubleType,true), StructField(C17,DoubleType,true), StructField(C18,DoubleType,true), StructField(C19,DoubleType,true), StructField(C20,DoubleType,true), StructField(C21,DoubleType,true), ...\ndf: org.apache.spark.sql.DataFrame = [C0: double, C1: double ... 98 more fields]\n"}]},"apps":[],"jobName":"paragraph_1504833929754_-1779366912","id":"20170512-112142_1828353367","dateCreated":"2017-09-07T18:25:29-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:10211","user":"admin","dateFinished":"2017-09-07T20:00:56-0700","dateStarted":"2017-09-07T20:00:51-0700"},{"text":"val minMaxMean =\n\"\"\"\nminOut = min(Xin)\nmaxOut = max(Xin)\nmeanOut = mean(Xin)\n\"\"\"","dateUpdated":"2017-09-07T20:01:02-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\n\n\n\n\n\nminMaxMean: String =\n\"\nminOut = mi
n(Xin)\nmaxOut = max(Xin)\nmeanOut = mean(Xin)\n\"\n"}]},"apps":[],"jobName":"paragraph_1504833929754_-1779366912","id":"20170512-113253_943926853","dateCreated":"2017-09-07T18:25:29-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:10212","user":"admin","dateFinished":"2017-09-07T20:01:02-0700","dateStarted":"2017-09-07T20:01:02-0700"},{"text":"val mm = new MatrixMetadata(numRows, numCols)\nval minMaxMeanScript = dml(minMaxMean).in(\"Xin\", df, mm).out(\"minOut\", \"maxOut\", \"meanOut\")","dateUpdated":"2017-09-07T20:01:05-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\nmm: org.apache.sysml.api.mlcontext.MatrixMetadata = rows: 1000, columns: 100, non-zeros: None, rows per block: None, columns per block: None\n\n\n\n\n\n\n\n\nminMaxMeanScript: org.apache.sysml.api.mlcontext.Script =\n
Inputs:\n [1] (Dataset as Matrix) Xin: [C0: double, C1: double ... 98 more fields]\n\nOutputs:\n [1] minOut\n [2] maxOut\n [3] meanOut\n"}]},"apps":[],"jobName":"paragraph_1504833929756_-1781675405","id":"20170512-113337_768342478","dateCreated":"2017-09-07T18:25:29-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:10213","user":"admin","dateFinished":"2017-09-07T20:01:14-0700","dateStarted":"2017-09-07T20:01:05-0700"},{"text":"val (min, max, mean) = ml.execute(minMaxMeanScript).getTuple[Double, Double, Double](\"minOut\", \"maxOut\", \"meanOut\")","dateUpdated":"2017-09-07T20:01:12-0700","config":{"colWidth":12,"editorMode":"ace/mode/scala","results":{},"enabled":true,"editorSetting":{"language":"scala"}},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\n\n\nmin: Double = 5.6206677819803375E-6\nmax: Double = 0.9999768801671057\nmean: Double = 0.5005588914625136\n"}]},"apps":[],"jobName":"paragraph_15048339
29756_-1781675405","id":"20170512-113424_1524717418","dateCreated":"2017-09-07T18:25:29-0700","status":"FINISHED","progressUpdateIntervalMs":500,"$$hashKey":"object:10214","user":"admin","dateFinished":"2017-09-07T20:01:17-0700","dateStarted":"2017-09-07T20:01:12-0700"},{"dateUpdated":"2017-09-07T18:25:29-0700","config":{"editorSetting":{"language":"scala"},"colWidth":12,"editorMode":"ace/mode/scala","results":{},"graph":{"mode":"table","height":300,"optionOpen":false,"keys":[],"values":[],"groups":[],"scatter":{}},"enabled":true},"settings":{"params":{},"forms":{}},"apps":[],"jobName":"paragraph_1504833929756_-1781675405","id":"20160407-215102_2146717979","dateCreated":"2017-09-07T18:25:29-0700","status":"READY","errorMessage":"","progressUpdateIntervalMs":500,"$$hashKey":"object:10215"}],"name":"tutorial1_zeppelin","id":"2CTM99W1A","angularObjects":{"2CK6XR78M:shared_process":[],"2CHZ7WYCF:shared_process":[],"2CKFJ7WPQ:shared_process":[],"2CKFPUHJ2:shared_process":[],"2C4U48MY3_sp
ark2:shared_process":[]},"config":{"looknfeel":"default","personalizedMode":"false"},"info":{}}
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